P–S–N Curve Fitting Method Based on Sample Aggregation Principle

Tan, Xiufeng

doi:10.1007/s11668-019-00586-1

Cited by 17 publications

(13 citation statements)

References 12 publications

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“…In order to verify the performance of the proposed method, the comparison in terms of precision and stability with the ISO method 27 has been conducted, which is a common method used to evaluate in comparison under small sample fatigue tests. 11,17,19 The performances of two methods are verified with fourpoint out-of-plane bending fatigue test data of carbon eight-harness-satin/epoxy laminate. 28 The general idea is to compare the performances of the two methods through different small sample strategies with respect to precision level.…”

Section: Verification and Discussionmentioning

confidence: 97%

New probabilistic S-N curves modeling method with small-sample test data of composite materials

Bai

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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Considering the large dispersion when processing small-sample fatigue test data of composite materials, a new method for modeling probabilistic S- N curves is proposed in terms of the equivalent fatigue lives. An equivalent fatigue life conversion model is first established based on two fundamental assumptions to improve the small-sample information utilized. Subsequently, a backward statistical inference technique improved by particle swarm optimization is used to determine probabilistic S- N curves through the equivalent fatigue lives. Finally, the proposed method is verified in terms of precision and stability by the fatigue test data of carbon eight-harness-satin/epoxy laminate. The results indicate that the proposed method can offer an accurate description of the probabilistic behavior of composite materials with small-sample test data.

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Section: Verification and Discussionmentioning

confidence: 97%

New probabilistic S-N curves modeling method with small-sample test data of composite materials

Bai

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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show abstract

“…In fact, the fatigue life of the same specimen under the same load is quite different, showing a certain dispersion, and the S‐N field or ε ‐ N field can be used to describe this dispersion of fatigue life. In recent years, a great deal of work has been done on how to establish accurate P ‐ S‐N curves ( P ‐ ε ‐ N curves) 24–26 . In 2014, Enrique Castillo's team 27 developed a software program ProFatigue for probabilistic assessment of experimental fatigue life, which greatly facilitates the drawing of S‐N field or ε ‐ N field.…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…In recent years, a great deal of work has been done on how to establish accurate P-S-N curves (P-ε-N curves). [24][25][26] In 2014, Enrique Castillo's team 27 developed a software program Pro-Fatigue for probabilistic assessment of experimental fatigue life, which greatly facilitates the drawing of S-N field or ε-N field.…”

Section: Analysis and Discussionmentioning

confidence: 99%

A new multiaxial fatigue life prediction method based on grey theory under small sample condition

Pan

Liu

et al. 2022

Fatigue Fract Eng Mat Struct

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It is always a challenge to accurately predict the fatigue life of specimens in engineering, and it is urgent to establish a convenient and accurate approach to estimate the fatigue life of specimens with different materials under small sample conditions. To solve the above problems, a new multiaxial fatigue life prediction method is proposed based on grey theory. First, established a modified MGM (1, N) model by fine-adjusting the time series based on the GM (1, N) model. Then the MGM (1, N) model is used to compare the results with different types of parameters, and the optimal gray prediction model is established based on the gray correlation analysis. The proposed method is verified by 79 test data of 10 kinds of materials including Q355(D), and the predicted results matched well with the experimental results. It displays that the method is reliable. Finally, the predicted results with an accuracy of more than 90% were fused with the test data to obtain a more accurate S-N field and ε-N field of Q355(D) based on small sample by the ProFatigue program.

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“…Therefore, the distributions of D C are the same at all stress levels. And according to the consistency principle of fatigue life percentile, 33 which means that a specimen which is “weak” at a high‐stress level would also be weak at a low‐stress level. The failure of a specimen will follow the Master S‐N curve.…”

Section: Reliability Model Establishment and Test Conditionsmentioning

confidence: 99%

Research on fatigue reliability prediction model and structural improvement of welded drive axle housing based on master S‐N Curve method

Tan

Wang

Xie

et al. 2022

Quality & Reliability Eng

Self Cite

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Fatigue reliability prediction of welded structures is mainly based on nominal stress or hot spot stress method, but there are some problems such as grid sensitivity and joint geometry dependence. The Master S-N curve method can solve these problems well, but the corresponding reliability model needs to be studied. In this paper, the fatigue reliability model of welded structures based on the Master S-N curve method is studied. Considering the randomness of life and the correlation of failure, a reliability model is proposed, which reduces the computational burden by establishing a median damage-random threshold rule. Taking the welded drive axle housing as an object, the system reliability is analyzed under the bench test condition, and verified by the experimental data. After the verification, this method is used to predict the reliability of the axle housing under variable amplitude loading collected in the test field, and the results are verified by Monte Carlo (MC) method. When the P-S-N curves are parallel, the model is accurate, which is the characteristic of the Master S-N curve method. This method only needs to input the median damage value of the weak part, which is easy to be applied. This method can speed up the reliability prediction cycle of welded structures, which is beneficial to product innovation and optimal design. Finally, an improved design scheme is proposed for the weak parts of welding, and the effects of welding leg width, welding depth, and closed weld on fatigue life are revealed.

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P–S–N Curve Fitting Method Based on Sample Aggregation Principle

Cited by 17 publications

References 12 publications

New probabilistic S-N curves modeling method with small-sample test data of composite materials

New probabilistic S-N curves modeling method with small-sample test data of composite materials

A new multiaxial fatigue life prediction method based on grey theory under small sample condition

Research on fatigue reliability prediction model and structural improvement of welded drive axle housing based on master S‐N Curve method

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